CN106373049A - Learning effort calculation method and realization apparatus - Google Patents
Learning effort calculation method and realization apparatus Download PDFInfo
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- CN106373049A CN106373049A CN201610563213.4A CN201610563213A CN106373049A CN 106373049 A CN106373049 A CN 106373049A CN 201610563213 A CN201610563213 A CN 201610563213A CN 106373049 A CN106373049 A CN 106373049A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/20—Education
- G06Q50/205—Education administration or guidance
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/166—Editing, e.g. inserting or deleting
- G06F40/174—Form filling; Merging
Abstract
The invention relates to a learning effort calculation method and realization apparatus. The method is characterized by comprising the steps of obtaining learning state data; performing statistics on the learning state data and calculating a feature value which reflects the size of the state data; calculating a duration value which reflects the length of the state data; and reflecting learning efforts by a product of the feature value and the duration value. According to the method and the apparatus, a calculation method for ''work'' in physics is introduced; the efforts in the state are described through the product of the state data and the duration time in a learning process; the meaning is definite; and a learning effort state can be well reflected. For example, the higher a product of a brain usage concentration degree and a brain usage duration time is, the higher the learning efforts are and the harder the learning is; the higher a product of a brain relaxation degree and a brain relaxation duration time is, the lower the learning efforts are and the not harder the learning is, so that the learning efforts can serve as learning negative work; during reading and writing, for the same time, the higher the eye use work is, the better an eye use distance is and the better a sitting posture is, so that the vision can be protected; and the lower the eye use work is, the shorter the eye use distance is, the worse the sitting posture is and the easier the occurrence of myopia is. In combination with a timetable or a curriculum schedule, colorful contents can be reflected.
Description
Technical field
The present invention relates to data statisticss are and in particular to a kind of learn diligent computational methods and realize device.
Background technology
People, in the requirement that children are learnt, often mention " study is diligent "." diligent " one in study
As be make great efforts consciousness, the head of a family wish oneself child study being capable of effort hard.Due to children's control phase
To poor, the situation of " lazy ", in learning process, often occurs, such as sluggishness is dilatory, absent minded etc..As
Fruit quantifies " diligent " in study, and to Students ' Learning, diligent situation is stated, and reflects its whether diligent or diligent state journey
Degree, can effectively help the study of children to improve.
Content of the invention
It is an object of the invention to provide a kind of learn diligent computational methods and realize device, by learning state data with hold
The product of continuous time carrys out numerology and commonly uses work(, reflects learning state.
One content of present inventive concept, a kind of diligent computational methods of study, its feature includes obtaining learning state data；
Statistical learning status data, calculates the eigenvalue reflecting described status data size；Calculate and reflect described status data length
Persistent value；Diligent with the product reflection study of persistent value with described eigenvalue.
Another content of present inventive concept, a kind of diligent computational methods of study realize device, including data acquisition list
Unit, processing unit, display unit, is characterized in that data capture unit obtains learning state data；Processing unit counts described shape
State data, calculates the eigenvalue reflecting described status data size；Calculate the persistent value reflecting described status data length；With institute
State eigenvalue diligent with the product reflection study of persistent value；Display unit shows the diligent result of calculation of described study.
The present invention quotes the computational methods of " work(" in physicss, by the status data in learning process and persistent period
Product is diligent under this state to describe, and meaning clearly, meets logic, can reflect the diligent situation of study very well.Such as
With brain focus and allowance be scope 0 ~ 100 numerical value, the higher explanation of focus more diligently, allowance higher explanation brain
Activity is fewer, and focus is higher with the product of its persistent period, illustrates that diligent degree is bigger, the more effort of performance, allowance with
The product of its persistent period is higher, illustrates more lazy, not making great efforts of performance, can be used as study negative work.For same
Learning time, study is higher hard, illustrates that the learning efficiency is higher, and learns lower hard, illustrates that study is dilatory, efficiency is relatively
Low.
Study in the present invention is not limited to use brain situation hard, and the use eye distance in also including learning is from, head pose etc..
Such as in reading writing, for same between at the moment, the work(with eye is higher, from better, sitting posture is better, profit for explanation eye distance
In protection vision, the work(with eye is lower, and close to more, sitting posture is poorer, easier myopia for explanation eye distance.For head pose it is then
The less head pose of its work(is more just.
The present invention is combined with daily schedule or curriculum schedule, can reflect colourful content, such as, shows one day
In every class the diligent state of study, the diligent state of study of contrast the English class and mathematics class, of statistics halves Chinese course
Commonly use account of somebody's meritorious service state, emphasis supervises the diligent situation of concrete study of daily English Class, be in when doing one's assignment, display different periods
Learn diligent state, and optimal study diligent situation and the diligent situation of worst study etc. in one day.With reference to concrete reality
Apply example to describe in detail.
Brief description
Fig. 1 is a kind of basic flow sheet learning diligent computational methods.
Fig. 2 is a kind of diligent cartogram of classroom brain focus.
Fig. 3 is a kind of classroom eye distance from cartogram.
Fig. 4 is the configuration block diagram that a kind of diligent computational methods of study realize device embodiment.
Specific embodiment
Learning state include with brain situation, with eye distance from, head pose, sitting posture etc., wherein include being absorbed in brain situation
Degree and allowance.Shown in Fig. 1 is a kind of learn diligent computational methods basic procedure, obtain learning state data first, to obtaining
Take status data to be counted, calculate the eigenvalue reflecting described status data size, calculate and reflect described status data length
Persistent value, diligent state is learnt with the reflection of the product of eigenvalue and persistent value.
Described eigenvalue is a center value, and the general characteristic of reflection status data, including meansigma methodss, mode, middle position
Number, harmonic mean, geometric mean；Described persistent value reflects status data length, including described status data accumulative when
Long, or the cumulative frequencies of described status data, if the acquisition time interval of learning state data is constant, cumulative frequencies and collection
The product at interval is equal to accumulative duration.
Further, it is possible to can set statistical condition to statistic behavior data, described statistical condition includes status data system
Meter section or statistical time range, given threshold.Statistics section is to carry out segmentation statistics to status data, and statistical time range is to state
Data counts at times, and given threshold is by a setting value, status data to be divided into by size more than given threshold and little
In two parts of given threshold, carry out statistical computation respectively.For the status data setting statistics section, its eigenvalue can be
By counting the value of calculation of section status data it is also possible to be directly section boundaries value or section intermediate value, for given threshold
Status data, its eigenvalue can be by statistics be not more than or not less than given threshold status data value of calculation, also may be used
To be directly given threshold.Eigenvalue as one analysis correction data, using same computational methods so as to result have comparable
Property.
Further, the diligent summation of study under each statistical condition can also be calculated, then the ratio divided by its persistent value summation
Value, reflects total learning efficiency.
Shown in Fig. 2 is the diligent cartogram of classroom brain focus, and statistical time range is the classroom period, and statistics given threshold is
40, count the absorbed degrees of data more than 40 in every class, calculate meansigma methodss as eigenvalue, count focus continuing more than 40
Time, diligent for this class brain focus with the product of persistent period with eigenvalue.It can be seen that four sections in the morning
In class, the diligent numerical value of the 4th class relatively low it may be possible to tired caused, afternoon first class minimum hard it may be possible to sleepy institute
Cause, taken a turn for the better to the second class mental status, risen with the diligent numerical value of brain focus.
Further, above-mentioned classroom learning is added up hard, be more than 40 divided by attend class total time or focus of the same day
Persistent period summation, can calculate the same day with brain focus efficiency.
Shown in Fig. 3 is classroom eye distance from cartogram, classroom eye distance from point 5 data segments records, respectively 15 ~
20cm, 20 ~ 25cm, 25 ~ 30cm, 30 ~ 35cm, 35 ~ 40cm, record falls into the use eye distance off-frequency number of each section, segmentation record
Status data form simple, data volume is little, and is easy to subsequent treatment.Using segmentation statistical method, section boundaries value can be taken
As eigenvalue, such as minimum boundary value 15,20,25,30,35cm, or maximum boundary value 20,25,30,35,40cm, or with section
Intermediate value as eigenvalue, respectively 17.5,22.5,27.5,32.5,37.5, statistics fall into the use eye distance of each section from
Cumulative frequencies are as time persistent value, diligent as this section eye with the product of persistent value using eigenvalue, then 5 sections
Eyes add up hard try to achieve classroom eyes diligent, then use the eye persistent period divided by classroom, show that the use eye of every class is imitated
Rate, reflect the main use eye distance of this class from.As stated above, carried out with eye efficiency (distance) in one day six class respectively
Calculate, draw out statistic histogram shown in Fig. 3 it can be seen that the characteristic similar to brain focus.
Optimize further, according to status data feature, described persistent value can be to no more than or not less than eigenvalue
Status data is counted, calculate reflect described status data length persistent value, for brain focus, with eye distance from permissible
Calculate the status data persistent value more than eigenvalue, head pose, sitting posture can calculate and continue less than the status data of eigenvalue
Value, by described eigenvalue and persistent value can calculate reflection particular state study is diligent or efficiency.Such as above-mentioned classroom is used
Brain focus, can count the focus persistent value more than meansigma methodss, with the product reflection of meansigma methodss and this focus persistent value
The focus of particular state is diligent.
Further, described persistent value can also include the accumulative duration of described status data and accounts for the ratio of total duration, or described
The cumulative frequencies of status data account for the ratio of total frequency, with the product of eigenvalue and persistent value accounting, can represent described statistical number
According to state efficiency.Above-mentioned use eye distance examples, the ratio accounting for total frequency with eye distance off-frequency number falling into each section can be calculated
As persistent value, calculate the product of each segment attribute value and persistent value accounting, then the product accumulation of 5 sections is tried to achieve often
The use eye distance of class is from efficiency.
Configuration block in figure shown in Fig. 4, including data capture unit, processing unit, display unit, data capture unit
Obtain learning state data, transmit processing unit statistical analysiss；Processing unit counts described status data, calculates and reflects described shape
The eigenvalue of state size of data；Calculate the persistent value reflecting described status data length；With taking advantage of of described eigenvalue and persistent value
Long-pending reflection study is diligent；Processing unit transmits display unit statistical computation result；Display unit shows study in graphical form
Diligent calculating data.
Learning state include with eye distance from, use brain situation, head pose, sitting posture, data capture unit can by study
State sensor gathers learning state data, is wherein gathered by range sensor with eye range data, uses eye range sensor
Including any one in infrared ambulator or ultrasonic range finder or laser range finder, such as infrared distance sensor
Gp2d12 investigative range 10 ~ 80cm, corresponding output 2.55 ~ 0.42v voltage, range finding is inversely proportional to voltage；Led to brain status data
Cross the collection of brain electric transducer, brain electric transducer includes single channel or multichannel sensor, brain is gathered using one pole or bipolar protocol
The signal of telecommunication, such as single channel eeg brain wave acquisition sensor thingkgear am family chip 512 EEG signals of collection per second
Data point, eight wave bands of output (delta, theta, lowalpha, highalpha, lowbeta, highbeta, lowgamma,
Middlegamma brain wave data), and three esense parameters: focus, allowance and nictation detecting；Head pose or
Sitting posture gathers attitude data by attitude transducer, and attitude transducer includes Gravity accelerometer or gyroscope, such as plus
Velocity sensor adxl345, for monitoring head pose, when head run-off the straight, gravity is in the gravity of three axial directions of x, y, z
Component output signal changes, and according to 3 weight component sizes axially exporting, can release 3 axial directions and vertical direction
Angle, thus calculate head inclination data.
Data capture unit can also receive the learning state data of learning state recording apparatus collecting, such as passes through
The wired modes such as rs232 or usb are directly connected to learning state recording equipment to obtain data, or wirelessly, such as
Status data in the reception/recording device such as infrared communication, the Internet, bluetooth, radio frequency, zigbee, wifi, or by storage
Card obtains data in recording equipment as medium.Data capture unit can be Internet Server, or smart mobile phone, or
Computer, or other has any one in the equipment of data receiver function.
Data processing unit can be Internet Server, or smart mobile phone, or computer, or other has number
According to any one in the equipment of processing function.
Display unit can be smart mobile phone, or computer, or other have arbitrary in the equipment of display function
Kind.
Whole device can be smart mobile phone, computer；Or display function is had by smart mobile phone, computer or other
Terminal and Internet Server constitute, server passes through Network Capture data, after server process, in mobile phone, computer
Or other has display in the terminal of display function.Including diligent for above-mentioned study computational methods are real on Internet Server
Apply, by network delivery data, there is in the other such as the portable data assistances such as smart mobile phone or computer the end of display function
Show on end, or in the other such as the portable data assistances such as smart mobile phone or computer, there is display learning diligent computational methods
Implement in the terminal of function.
Claims (10)
1. the diligent computational methods of a kind of study, its feature includes:
(1) obtain learning state data；
(2) count described learning state data, calculate the eigenvalue reflecting described status data size；Calculate and reflect described state
The persistent value of data length；
(3) diligent with the product reflection study of persistent value with described eigenvalue.
2. method according to claim 1, is characterized in that: described statistics includes setting statistical condition, described statistical condition bag
One of include status data statistics section, or statistical time range, or given threshold.
3. method according to claim 1, is characterized in that: described eigenvalue includes the meansigma methodss of status data, mode, middle position
Number, harmonic mean, one kind of geometric mean.
4. method according to claim 1 or claim 2, is characterized in that: described eigenvalue includes status data statistics section boundaries value
Or section intermediate value, or given threshold.
5. method according to claim 1, is characterized in that: described persistent value is the status number no more than or not less than eigenvalue
According to persistent value, reflect described status data length.
6. according to claim 1 or 5 methods describeds, it is characterized in that: described persistent value includes the accumulative duration of described status data,
Or the cumulative frequencies of described status data.
7. according to claim 1 or 5 methods describeds, it is characterized in that: described persistent value includes the accumulative duration of described status data
Account for the ratio of total duration, or the cumulative frequencies of described status data account for the ratio of total frequency.
8. method according to claim 1, is characterized in that: methods described includes numerology, and to commonly use work(summation total divided by persistent value
The ratio of sum, reflects the learning efficiency.
9. one kind realizes device, including data capture unit, process according to the described diligent computational methods of one of claim 1 ~ 8
Unit, display unit, is characterized in that:
(1) data capture unit obtains learning state data；
(2) processing unit counts described status data, calculates the eigenvalue reflecting described status data size；Calculate reflection described
The persistent value of status data length；Diligent with the product reflection study of persistent value with described eigenvalue；
(3) display unit shows the diligent result of calculation of described study.
10. device according to claim 9, is characterized in that: described display unit shows that described study is diligent in graphical form.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510429266 | 2015-07-21 | ||
| CN2015104292662 | 2015-07-21 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106373049A true CN106373049A (en) | 2017-02-01 |
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ID=57880768
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| Application Number | Title | Priority Date | Filing Date |
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| CN201610563213.4A Pending CN106373049A (en) | 2015-07-21 | 2016-07-18 | Learning effort calculation method and realization apparatus |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107714012A (en) * | 2017-10-30 | 2018-02-23 | 浙江师范大学 | A kind of intelligent necklace based on sitting posture and rhythm of the heart reflection learner's state |
| CN108805762A (en) * | 2018-05-23 | 2018-11-13 | 深圳市心流科技有限公司 | Instruction analysis method, server and computer readable storage medium |
| CN110345872A (en) * | 2019-06-27 | 2019-10-18 | 浙江天地人科技有限公司 | A kind of horizontal judgment method of learning state |
-
2016
- 2016-07-18 CN CN201610563213.4A patent/CN106373049A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107714012A (en) * | 2017-10-30 | 2018-02-23 | 浙江师范大学 | A kind of intelligent necklace based on sitting posture and rhythm of the heart reflection learner's state |
| CN108805762A (en) * | 2018-05-23 | 2018-11-13 | 深圳市心流科技有限公司 | Instruction analysis method, server and computer readable storage medium |
| CN110345872A (en) * | 2019-06-27 | 2019-10-18 | 浙江天地人科技有限公司 | A kind of horizontal judgment method of learning state |
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Application publication date: 20170201 |
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